Lead Data Engineer

JGA Recruitment Group | B Corp
London
3 days ago
Create job alert

Lead Data Engineer


Tech Stack: Python | Spark | Kafka | Airflow | Vector DBs

Location: London - office based

Salary: Up to £140k + equity


We’re partnering with a well-funded AI startup building a category-defining platform within a major UK industry undergoing rapid transformation.


This is a first data hire and a genuinely high-impact role, owning and building the entire data infrastructure from the ground up.


You’ll work closely with AI and engineering teams to design scalable data pipelines, support machine learning systems, and enable real-time, intelligent decision-making across the platform.


What you’ll be doing:

• Building and scaling modern data pipelines (batch + real-time)

• Designing data architecture across relational, NoSQL, and vector databases

• Supporting ML workflows and AI-driven products

• Driving performance, scalability, and data reliability

• Influencing technical strategy in a fast-growing environment


What we’re looking for:

• 7+ years in Data / Backend Engineering

• Strong Python and distributed systems experience

• Hands-on with modern data tooling (Spark, Airflow, Kafka, etc.)

• Experience with relational + NoSQL databases (vector DBs a big plus)

• Comfortable in a fast-paced, early-stage environment


💡 High ownership, strong engineering culture, and meaningful equity on offer.


Apply or message me directly for more details.


JGA are dedicated to delivering the best possible candidate experience. Due to the high volume of applications, we regret that we are not always able to respond to every individual applicant. If your application is shortlisted, a member of our team will be in touch. Thank you for your understanding.


JGA Recruitment Group Ltd ("We") are committed to equality of opportunity for all applications regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships. We strongly encourage suitably qualified applicants from a wide range of backgrounds to apply.


We are also committed to protecting and respecting your privacy. We are a specialist Payroll and HR recruitment agency and recruitment business as defined in the Employment Agencies and Employment Businesses Regulations 2003 (our business). These statements together with our privacy notices set out the basis on which any personal data we collect from you, or that you provide to us, will be processed by us.

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer (AWS & Snowflake)

Lead Data/Head of Data Engineer

Lead Data Engineer (Snowflake)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.